Relevance Ranking in Primo

Ex Libris Primo® enables library users to discover and access billions of global and local scholarly resources. The constantly growing collections available through Primo Central consist of both traditional and modern scholarly materials, including journal articles, books, ebooks, videos, newspapers, images, reviews, datasets, and more.
How does Primo provide patrons and researchers the most relevant list of results?


Relevance Ranking: Primo ScholarRankIntelligent Ranking Technology

Search and ranking technology relies on a multitude of factors and parameters to understand the user’s intent and provide results that meet the user’s expectations. The Primo relevance ranking mechanism leverages ScholarRank™ technology to sort search results by relevance on the basis of several criteria:

The degree to which an item matches the query
For example,
Primo attaches greater relevancy to an item if the query terms occur in specific metadata fields of the item’s record—primarily the author, title, and subject fields—and if the order of the query terms or phrases is the same in the query and in the record.

A value score representing an item’s academic significance
The item’s academic significance is calculated based on factors unrelated to the query, such as whether the item was published in a peer-reviewed journal, how many times it has been cited, and what type of material it is, for example an academic journal article as opposed to a newspaper article. 

An item’s relevance to the user’s specific query and profile
Primo infers the type of search that the user is conducting, such as a known-item search or a broad-topic search, and takes the type of material into account. In broad-topic searches (for example social intelligence, mining engineering,or operator theory)in which a user usually has no specific item in mind, Primo provides a “mixed result list,” with overview material, such as reference and introductory material, on top, followed by more specialized research articles. In known-item searches, Primo bases its search results on author names, exact titles, or other variations, such as the citation as a whole, to boost the appropriate item to the top of the result list. Large scale log analysis and usability studies are the core sources for identifying and defining such search types, and for understanding the variations and their significance.

The publication date (recentness) of an item
Primo takes into account that users usually prefer newer materials.

Personalized ranking
Primo enables users to tailor their result lists to their field of interest. This feature is especially useful when queries are relevant to various disciplines. Primo can apply information about a user’s area of study to boost materials related to that discipline.

Adjusting Relevance Ranking of Local Collections

Allowing libraries greater flexibility and control, Primo enables libraries to adjust settings for the relevance ranking of their own local materials. First, a library can boost certain metadata fields to give them more weight in the equation. Secondly, a library that chooses to blend results from different sources into a single result list—for example, to blend Primo Central results with results from local collections—can boost local items so that they appear higher on the result list than items coming from Primo Central, all other factors being equal.

Ex Libris continuously enhances and optimizes the Primo relevance ranking technology based on analysis of search log analyses, user studies, customer feedback, and input from the Primo customer community.

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